In order to improve the work efficiency of non-destructive testing(NDT)and the reliability of NDT results,an automatic method to detect defects in the ultrasonic image was researched.According to the characterization of ultrasonic D-scan image,clutter wave suppression and de-noising were presented firstly.Then,the image is processed by binaryzation using KSW 2 D entropy based on image segmentation method.The results showed that,the global threshold based segmentation method was somewhat ineffective for D-scan image because of under-segmentation.Especially,when the image is big in size,small targets which are composed by a small amount of pixels are often undetected.Whereas,local threshold based image segmentation method is effective in recognizing small defects because it takes local image character into account.
针对常规超声TOFD法存在近表面检测盲区的问题,提出一种纵波三次反射的TOFDW检测模式.分析了TOFDW模式的声传播特性,并阐明了该模式的检测原理.通过人工缺陷检测,研究了该模式检测信号和图像特征及检测灵敏度和精度.对实际焊缝进行了检测,并通过破坏性试验对无损检测结果进行了验证.结果表明,TOFDW模式能够识别常规模式下无法辨别的近表面缺陷,可有效检测到埋藏深度1.0 mm的人工缺陷;同时,该模式具有较高的量化测量精度,近表面人工缺陷埋藏深度测量的平均绝对误差不超过0.3 mm.
Brazed weldment with lattice structure has been widely used in aerospace industry. The non-destructive testing is often difficult because of the poor inspection accessibility. The present paper illustrates how the plane-like defect lack of brazing can be detected rapidly in this kind of structure by using ultrasonic Lamb wave. Experimental weldments are prepared and weld defect are tested using S2 mode Lamb wave. Acoustic shadow technique is employed based on Lamb wave testing method. The character of the tested D-scan image and A-scan signal is studied. The experimental results show that acoustic shadow based Lamb wave testing method is effective in detecting through-wall lack of brazing. Meanwhile, the D-scan tested data can be rapidly collected and easily interpreted compared with pulse echo bused Lamb wave testing method.
In ultrasonic time of flight diffraction （TOFD） D-scan image, only a small fraction represents defects, whereas the majority is redundant. Because of the low contrast between defect and background image, it is difficult to manually interpret TOFD image. In addition, due to the nature of the weak amplitude of ultrasonic diffracted signals, the human factor introduces inconsistency into the interpretation. In order to automatically distinguish weld defects from the D-scan image, a defect detection method based on image processing technique is proposed. First, image pre-processing including clutter and noise suppression is conducted. Second, information entropy based image segmentation technique is employed to extract defects in the pre-processed image. At last, mathematical morphology based post-processing is carried out. The experimental results show that with the proposed method, TOFD can be used for automatic weld defect detection with satisfactory level of reliability.
